Scientific - Data Scientist
Apply NowCompany: Futran Tech Solutions Pvt. Ltd.
Location: Lawrence Township, NJ 08648
Description:
Scientific - Data Scientist
Location - Lawrenceville, New Jersey 08648
Role is 100% onsite.
Junior (0-3 Yrs.)
Description
Leads discovery and optimization (LDO) is a diverse group of scientists and engineers, providing critical assay information to therapeutic research centers (TRCs) throughout research and early development (R&ED). We are seeking a highly motivated and innovative data scientist to join the data science and advanced analytics team within LDO until the end of 2023. The individual will develop a machine learning and Bayesian statistics-based approach to model assay variability using medium to high throughput screening datasets. The individual will work in a highly dynamic environment at the center of the R&ED drug discovery engine to develop cutting edge tools applied to complex drug discovery problems.
Roles and Responsibilities
Write python scripts to enable rapid cleaning and analysis of medium and high throughput datasets
Utilize machine learning (ML) approaches to generate small molecules features
Utilize Bayesian statistics approaches to estimate uncertainties in assay datasets, based on results on above ML outputs
Write and document programming code (python preferred) to facilitate data preparation / cleaning, model development, and evaluation
Produce high quality scripts, documentation, and processing pipeline by the end of 2023
Create deployable version of processing pipeline for near term use as a stand-alone application and ultimately future integration with enterprise suite
Qualifications
Ph.D. in quantitative sciences/engineering (computer science, mathematics, statistics, or engineering)
5+ years of relevant professional experience with a proven track record in machine learning and data science - experience in drug discovery machine learning is desirable but not required
Strong knowledge of one or more scripting programming languages, with a focus on machine learning (e.g., Python (preferred), R, Matlab, C/C++)
Experience utilizing molecular features of small molecules in machine learning models
Experience with the use and application of Bayesian statistics and simulation methods in generating probabilistic outcomes
Able to extract information from databases using a variety of software packages (e.g., Oracle SQL developer)
Ability to build and maintain databases aligned with enterprise solutions is desirable but not required
Strong analytical and problem solving skills to understand technical business problems and implement solutions
Ability to work effectively on matrixed teams to collaboratively solve challenging problems, while also able to work independently with minimal resources
Has good interpersonal, communication, writing and organizational skills
Strong preference for on-site presence to enable colocation with data science team
Location - Lawrenceville, New Jersey 08648
Role is 100% onsite.
Junior (0-3 Yrs.)
Description
Leads discovery and optimization (LDO) is a diverse group of scientists and engineers, providing critical assay information to therapeutic research centers (TRCs) throughout research and early development (R&ED). We are seeking a highly motivated and innovative data scientist to join the data science and advanced analytics team within LDO until the end of 2023. The individual will develop a machine learning and Bayesian statistics-based approach to model assay variability using medium to high throughput screening datasets. The individual will work in a highly dynamic environment at the center of the R&ED drug discovery engine to develop cutting edge tools applied to complex drug discovery problems.
Roles and Responsibilities
Write python scripts to enable rapid cleaning and analysis of medium and high throughput datasets
Utilize machine learning (ML) approaches to generate small molecules features
Utilize Bayesian statistics approaches to estimate uncertainties in assay datasets, based on results on above ML outputs
Write and document programming code (python preferred) to facilitate data preparation / cleaning, model development, and evaluation
Produce high quality scripts, documentation, and processing pipeline by the end of 2023
Create deployable version of processing pipeline for near term use as a stand-alone application and ultimately future integration with enterprise suite
Qualifications
Ph.D. in quantitative sciences/engineering (computer science, mathematics, statistics, or engineering)
5+ years of relevant professional experience with a proven track record in machine learning and data science - experience in drug discovery machine learning is desirable but not required
Strong knowledge of one or more scripting programming languages, with a focus on machine learning (e.g., Python (preferred), R, Matlab, C/C++)
Experience utilizing molecular features of small molecules in machine learning models
Experience with the use and application of Bayesian statistics and simulation methods in generating probabilistic outcomes
Able to extract information from databases using a variety of software packages (e.g., Oracle SQL developer)
Ability to build and maintain databases aligned with enterprise solutions is desirable but not required
Strong analytical and problem solving skills to understand technical business problems and implement solutions
Ability to work effectively on matrixed teams to collaboratively solve challenging problems, while also able to work independently with minimal resources
Has good interpersonal, communication, writing and organizational skills
Strong preference for on-site presence to enable colocation with data science team